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Metro location with broad ML/AI and MLOps requirements, but senior 12+ years reduces applicant density.
Requires specialized ML/AI, LLM and insurance consulting experience, making cross-industry transferability limited.
Explicit 12+ years, deep ML/AI, MLOps, and specified tech stack make filters highly stringent.
Provide technical direction across data science projects including data modeling, predictive modeling, reporting, and automation throughout the insurance value chain.
Lead client working sessions and project status meetings, managing day-to-day project operations to meet client expectations.
Serve as functional and domain expert for projects, ensuring delivery quality and client satisfaction, with responsibility over analytics teams including career management and training.
12+ years of core analytics experience in Data Science, Gen-AI, Large Language Models, ML-AI Model Development, and Data Engineering with consulting/implementation experience, preferably in Life Insurance.
Bachelor’s or master’s degree (or equivalent) in economics, mathematics, computer science/engineering, operations research, or related analytics field from a top-tier institution.
Technical expertise in Python, SQL, Tableau, Power BI, cloud data storage (Snowflake/S3/ADLS Gen2), MLOps tools (MLflow, Airflow, Docker, Kubernetes), and working knowledge of cloud platforms (AWS/Azure/GCP).
Experience managing dual shore engagements and direct client management.
Experienced leader capable of managing and mentoring offshore analytics teams in a fast-paced, evolving consulting environment.
Strong domain expertise in insurance analytics, specifically life insurance, with demonstrated ability to handle cross-cultural client interactions globally.
Proven technical and managerial skills combining advanced data science, cloud technology, and MLOps, with a hands-on approach and entrepreneurial mindset.